As new technology is integrated into day-to-day operations, the problem of system failure can become more acute. If a complex system fails, the cost to diagnose and fix the problem can dramatically reduce the system's value. While every system strives to be robust and reliable, failure rates for electro-mechanical systems will never reach zero. Instead, failure risk can be more effectively mitigated by engineering systems that can predict and diagnose their own failures, allowing users to take mitigating action before the system becomes unusable. This will allow users to integrate new technology with confidence that it will work when they need it.
Naïve self-diagnosing technology is all around us already: operating systems tell the user that they have “encountered” an error, cellular phones estimate signal strength with “bars,” and GPS navigation units tell the user that they have “lost satellite reception.” However, these diagnoses are typically opaque and late: the user only learns of the failure after it has occurred and must figure out for himself what mitigating action to take. While this may be acceptable for cell phones and laptops, a more predictive system with better diagnosis can be desirable or even necessary.